231 lines
6.5 KiB
Markdown
231 lines
6.5 KiB
Markdown
# aman
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> Local amanuensis
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Python X11 STT daemon that records audio, runs Whisper, applies local AI cleanup, and injects text.
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## Requirements
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- X11
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- `sounddevice` (PortAudio)
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- `faster-whisper`
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- `llama-cpp-python`
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- Tray icon deps: `gtk3`, `libayatana-appindicator3`
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- Python deps (core): `numpy`, `pillow`, `faster-whisper`, `llama-cpp-python`, `sounddevice`
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- X11 extras: `PyGObject`, `python-xlib`
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System packages (example names): `portaudio`/`libportaudio2`.
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<details>
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<summary>Ubuntu/Debian</summary>
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```bash
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sudo apt install -y portaudio19-dev libportaudio2 python3-gi gir1.2-gtk-3.0 libayatana-appindicator3-1
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```
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</details>
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<details>
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<summary>Arch Linux</summary>
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```bash
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sudo pacman -S --needed portaudio gtk3 libayatana-appindicator
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```
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</details>
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<details>
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<summary>Fedora</summary>
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```bash
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sudo dnf install -y portaudio portaudio-devel gtk3 libayatana-appindicator-gtk3
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```
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</details>
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<details>
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<summary>openSUSE</summary>
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```bash
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sudo zypper install -y portaudio portaudio-devel gtk3 libayatana-appindicator3-1
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```
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</details>
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## Python Daemon
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Install Python deps:
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X11 (supported):
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```bash
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uv sync --extra x11
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```
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## Config
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Create `~/.config/aman/config.json` (or let `aman` create it automatically on first start if missing):
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```json
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{
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"daemon": { "hotkey": "Cmd+m" },
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"recording": { "input": "0" },
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"stt": { "model": "base", "device": "cpu" },
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"injection": {
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"backend": "clipboard",
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"remove_transcription_from_clipboard": false
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},
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"vocabulary": {
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"replacements": [
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{ "from": "Martha", "to": "Marta" },
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{ "from": "docker", "to": "Docker" }
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],
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"terms": ["Systemd", "Kubernetes"]
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}
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}
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```
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Recording input can be a device index (preferred) or a substring of the device
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name.
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Hotkey notes:
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- Use one key plus optional modifiers (for example `Cmd+m`, `Super+m`, `Ctrl+space`).
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- `Super` and `Cmd` are equivalent aliases for the same modifier.
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- Invalid hotkey syntax in config prevents startup/reload.
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- When `~/.config/aman/pipelines.py` exists, hotkeys come from `HOTKEY_PIPELINES`.
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- `daemon.hotkey` is used as the fallback/default hotkey only when no pipelines file is present.
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AI cleanup is always enabled and uses the locked local Llama-3.2-3B GGUF model
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downloaded to `~/.cache/aman/models/` during daemon initialization.
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Use `-v/--verbose` to enable DEBUG logs, including recognized/processed
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transcript text and llama.cpp logs (`llama::` prefix). Without `-v`, logs are
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INFO level.
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Vocabulary correction:
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- `vocabulary.replacements` is deterministic correction (`from -> to`).
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- `vocabulary.terms` is a preferred spelling list used as hinting context.
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- Wildcards are intentionally rejected (`*`, `?`, `[`, `]`, `{`, `}`) to avoid ambiguous rules.
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- Rules are deduplicated case-insensitively; conflicting replacements are rejected.
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STT hinting:
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- Vocabulary is passed to Whisper as `hotwords`/`initial_prompt` only when those
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arguments are supported by the installed `faster-whisper` runtime.
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## systemd user service
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```bash
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mkdir -p ~/.local/share/aman/src/assets
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cp src/*.py ~/.local/share/aman/src/
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cp src/assets/*.png ~/.local/share/aman/src/assets/
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cp systemd/aman.service ~/.config/systemd/user/aman.service
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systemctl --user daemon-reload
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systemctl --user enable --now aman
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```
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## Usage
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- Press the hotkey once to start recording.
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- Press it again to stop and run STT.
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- Press `Esc` while recording to cancel without processing.
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- Transcript contents are logged only when `-v/--verbose` is used.
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- Config changes are hot-reloaded automatically (polled every 1 second).
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- `~/.config/aman/pipelines.py` changes are hot-reloaded automatically (polled every 1 second).
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- Send `SIGHUP` to force an immediate reload of config and pipelines:
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`systemctl --user kill -s HUP aman` (or send `HUP` to the process directly).
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- Reloads are applied when the daemon is idle; invalid updates are rejected and the last valid config stays active.
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- Reload success/failure is logged, and desktop notifications are shown when available.
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Wayland note:
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- Running under Wayland currently exits with a message explaining that it is not supported yet.
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Injection backends:
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- `clipboard`: copy to clipboard and inject via Ctrl+Shift+V (GTK clipboard + XTest)
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- `injection`: type the text with simulated keypresses (XTest)
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- `injection.remove_transcription_from_clipboard`: when `true` and backend is `clipboard`, restores/clears the clipboard after paste so the transcript is not kept there
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AI processing:
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- Local llama.cpp model only (no remote provider configuration).
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## Pipelines API
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`aman` is split into:
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- shell daemon: hotkeys, recording/cancel, and desktop injection
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- pipeline engine: `lib.transcribe(...)` and `lib.llm(...)`
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- pipeline implementation: Python callables mapped per hotkey
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Pipeline file path:
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- `~/.config/aman/pipelines.py`
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- You can start from [`pipelines.example.py`](./pipelines.example.py).
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- If `pipelines.py` is missing, `aman` uses a built-in reference pipeline bound to `daemon.hotkey`.
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- If `pipelines.py` exists but is invalid, startup fails fast.
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- Pipelines are hot-reloaded automatically when the module file changes.
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- Send `SIGHUP` to force an immediate reload of both config and pipelines.
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Expected module exports:
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```python
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HOTKEY_PIPELINES = {
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"Super+m": my_pipeline,
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"Super+Shift+m": caps_pipeline,
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}
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PIPELINE_OPTIONS = {
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"Super+Shift+m": {"failure_policy": "strict"}, # optional
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}
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```
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Pipeline callable signature:
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```python
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def my_pipeline(audio, lib) -> str:
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text = lib.transcribe(audio)
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context = lib.llm(
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system_prompt="context system prompt",
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user_prompt=f"Transcript: {text}",
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)
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out = lib.llm(
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system_prompt="amanuensis prompt",
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user_prompt=f"context={context}\ntext={text}",
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)
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return out
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```
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`lib` API:
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- `lib.transcribe(audio, hints=None, whisper_opts=None) -> str`
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- `lib.llm(system_prompt=..., user_prompt=..., llm_opts=None) -> str`
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Failure policy options:
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- `best_effort` (default): pipeline errors return empty output
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- `strict`: pipeline errors abort the current run
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Validation:
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- `HOTKEY_PIPELINES` must be a non-empty dictionary.
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- Every hotkey key must be a non-empty string.
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- Every pipeline value must be callable.
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- `PIPELINE_OPTIONS` must be a dictionary when provided.
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Reference behavior:
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- The built-in fallback pipeline (used when `pipelines.py` is missing) uses `lib.llm(...)` twice:
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- first to infer context
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- second to run the amanuensis rewrite
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- The second pass requests JSON output and expects `{"cleaned_text": "..."}`.
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- Deterministic dictionary replacements are then applied as part of that reference implementation.
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Control:
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```bash
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make run
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make check
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```
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